About this workshop

1 About us (Paul & Jonas)

Paul
- Currently MZES Research fellow (University of Mannheim)
- Previously… University of Bern (PhD, 2015), European University Institute (Postdoc, 15’-17’)
- My research interests: political sociology & methodology [see Google Scholar)
- Started R around 2009, first shiny apps ~2015 for teaching/research purposes (e.g., here and here)
- Contact: mail@paulcbauer.de; www.paulcbauer.de; Twitter; Github
Jonas
- Currently a research fellow at GESIS’ survey data curation (SDC) department
- Constantly learning about R and Shiny since 2020
- Interested in social geography, spatial analysis and computational text analysis
- Contact: jonas.lieth@gesis.org; GitHub: JsLth

2 Your turn

Let’s check our the survey results…

Name?
Affiliation? Country?
What do you want to use Shiny for? (or research questions?)

3 Contact & Outline & Dates

Important: 1st time we teach workshop/material
Course outline/content/dates: (see toc on the left)
- Day 1: Introduction to Shiny
  - 13:00 - 14:00: Welcome and Introduction (1)
  - 14:00 - 15:00: Introduction (2)
  - 15:00 - 15:30: Coffee break
  - 15:30 - 16:30: User Interface (UI): Designing the front end (1)
  - 16:30 - 17:30: User Interface (UI): Designing the front end (2) [Introduction tab]
- Day 2: Reactive programming
  - 13:00 - 14:00: Server: Reactive programming (1)
  - 14:00 - 15:00: Server: Reactive programming (2) [Tabulate data tab]
  - 15:00 - 15:30: Coffee break
  - 15:30 - 16:30: Modelling and visualizing data (1)
  - 16:30 - 17:30: Modelling and visualizing data (2) [Modelling data tab]
- Day 3: Develop your app
  - 13:00 - 14:00: Mapping data & advanced visualization (1)
  - 14:00 - 15:00: Mapping data & advanced visualization (2) [Mapping data tab]
  - 15:00 - 15:30: Coffee break
  - 15:30 - 16:30: Theming & styling
  - 16:30 - 17:30: Strengthen & Deploy

4 Script & material

Literature: See syllabus.
Website/script: https://bookdown.org/paul/shiny_workshop/
- Find it: Google “shiny paul jonas”
- Document = slides + script (Zoom in/out with STRG + mousewheel)
- Code: can all be found in the script
- Data: can usually be downloaded over links in the script. If not we’ll share the files.
- Full screen: F11
- Navigation: TOCs on left and right
- Search document (upper left)
- Document generated with quarto
Motivation: Have a go-to script for participants (and ourselves!)
Content: Mixture of theory, lab sessions, exercises and pure code examples for discussion

5 Strategy & Goals

Strategy: From the simple to the complex, slowly building up a complex Shiny app that includes various aspects (tabulate data, modelling and descriptive graphs, mapping)
Goals: By the end of the course participants will:
- know what the structure of a Shiny application looks like
- understand the basics of reactive programming for interactive data analysis and visualization
- be comfortable to use R Shiny to build their own interactive applications
- have learned about different ways to launch their Shiny application

6 Online vs. offline

Negative
- Screen fatigue
- Can’t run around to check your code
- Less engaging, less social
- Voice
- Screen sharing &less screen space than classroom
Positive
- We see the Shiny app how its mostly consumed ;-) (on a screen)
  - Remember: “How is your Shiny app consumed (smartphone)?”
- Participation from everywhere
Rule(s): Please keep your camera online if possible!
- Distracting animals/children/partners are a welcome distraction!
- Yawning, leaving, looking bored etc. allowed!
- Use a virtual background if you like!

7 Recommended readings

Important: Our workshop does not require any prior reading.
However, our schedule is primarily based on two textbooks which we generally recommend for further reading (see references on website):
- Wickham (2021): Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R. Accessible online at: https://mastering-shiny.org/.
- Fay, Colin, Rochette, Sébastien, Guyader, Vincent, and Girard, Cervan (2022): Engineering Production-Grade Shiny Apps. Accessible online at: https://engineering-shiny.org/.

8 Software we will use

Open-source software! (Q: Why?)
R (R Core Team 2023)¹
- only viable competitor is Python
- Install the necessary packages using the code below.

# install.packages('pacman')
library(pacman)
p_load('gt', 'gtsummary',
'modelsummary', 'gifski', 'png', 'datasauRus', 'ggplot2', 'gganimate', 'dplyr',
'shiny', 'htmltools', 'bs4Dash', 'fresh', 'waiter', 'shinyWidgets', 'Guerry',
'sf', 'tidyr', 'RColorBrewer', 'viridis', 'leaflet', 'plotly', 'jsonlite',
'GGally', 'datawizard', 'parameters', 'performance', 'ggdark', 'reactlog',
'profvis', 'rsconnect', 'whereami', 'DT')

Shiny (Chang et al. 2022; Wickham 2021)
Ggplot2² (Wickham 2016)
Plotly³ (Sievert 2020)
Note: Ideally cite the software you use in your research especially when it is open-source (e.g., run citation("ggplot2"))

9 Helpful resources

References

Chang, Winston, Joe Cheng, JJ Allaire, Carson Sievert, Barret Schloerke, Yihui Xie, Jeff Allen, Jonathan McPherson, Alan Dipert, and Barbara Borges. 2022. Shiny: Web Application Framework for r. https://CRAN.R-project.org/package=shiny.

R Core Team. 2023. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Sievert, Carson. 2020. Interactive Web-Based Data Visualization with r, Plotly, and Shiny. Chapman; Hall/CRC. https://plotly-r.com.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.

———. 2021. Mastering Shiny. " O’Reilly Media, Inc.".

Footnotes

Creators: Core contributors and thousands of package authors.↩︎
Creators: https://github.com/tidyverse/ggplot2↩︎
Creators: https://github.com/plotly/plotly.js; https://github.com/ropensci/plotly↩︎